Leaflet with R

Leaflet is an open source JavaScript library for ineracticve maps:

• has built in basic interactivity like zoom, pan and markers
• can handle shape files using the rgdal package
• can integrate with Shiny app.

library(maps)

package <U+393C><U+3E31>maps<U+393C><U+3E32> was built under R version 3.5.3

m <- leaflet() %>%
  
  setView(lng = 145.0431, lat = -37.8773, zoom = 15) %>% 
  addTiles()
            
m

NA

Note: that the use of %>% basically means use the result of the previous function as the first parameter of the next function.

The magrittr package offers a set of operators which make your code more readable by:

• structuring sequences of data operations left-to-right (as opposed to from the inside and out),
• avoiding nested function calls,
• minimizing the need for local variables and function definitions, and
• making it easy to add steps anywhere in the sequence of operations.

Is the equiv of writing:

#call the functionality of leaflet
m <- leaflet()
#set where the map is
m <- setView(m,
             lng = 145.0431, lat = -37.8773, zoom = 15) 
#Add graphics elements and layers to the map widget
m <- addTiles(m)
  
m

Customise the tile

Leaflet providers

use help(addProviderTiles) to check other available tiles.

m %>% addProviderTiles("Stamen.TonerLite")

Placing Markers on Leaflet Maps

#read some data
data <- read.csv("vet_schools_in_victoria.csv")
head(data)

#dataset is very large so only place the first 30 record
leaflet(data = data[1:30, ] ) %>%
  
  #add the map
  addTiles() %>%
  
  #add some markers
  addMarkers(~longitude, #x values
             ~latitude, #y values
             
             #label that pops up when you click
             popup= ~as.character(location))

Now plot all the data:

leaflet(data = data) %>%
  
  addTiles() %>%
  
  addMarkers(~longitude, #x values
             ~latitude, #y values
             
             #label that pops up when you click
             popup= ~as.character(location),
             
             #cluster markers when zooming out and in
             clusterOptions = markerClusterOptions())

Plotting Choropleth Maps with Leaflet

#preprocess that data
data <- read.csv("Household-heating-by-State-2008.csv", header=T) 
head(data)

#change the name of column 4 (X..Housing.Units.That.Are.Mobile.Homes) to Mobile homes
names(data)[4]<- "MobileHomes"
ag <- aggregate(MobileHomes~ States, #group by state
                FUN = mean, #find the mean number of mobile homes
                data = data) #in the data dataset
#make lower case as map data (see below) uses lower case!
ag$States <- tolower(ag$States)
head(ag)

mapStates <- map("state", 
                  fill = TRUE, 
                  plot = FALSE)
#find the related rate for each state
rates <- ag$MobileHomes[match(mapStates$names, ag$States)]
#map the data
cpal <- colorNumeric("Blues", rates) # prepare the color mapping
#create the blak cavas
leaflet(mapStates) %>%
  
  addTiles() %>%
  
  addPolygons(
    stroke = FALSE,
    smoothFactor = 0.2,
    fillOpacity = 1,
    
    #use the rate of each state to find the correct colour
    color = ~cpal(rates)
  )

Not all the states appear…

#print variables
mapStates$names

 [1] "alabama"                         "arizona"                         "arkansas"                       
 [4] "california"                      "colorado"                        "connecticut"                    
 [7] "delaware"                        "district of columbia"            "florida"                        
[10] "georgia"                         "idaho"                           "illinois"                       
[13] "indiana"                         "iowa"                            "kansas"                         
[16] "kentucky"                        "louisiana"                       "maine"                          
[19] "maryland"                        "massachusetts:martha's vineyard" "massachusetts:main"             
[22] "massachusetts:nantucket"         "michigan:north"                  "michigan:south"                 
[25] "minnesota"                       "mississippi"                     "missouri"                       
[28] "montana"                         "nebraska"                        "nevada"                         
[31] "new hampshire"                   "new jersey"                      "new mexico"                     
[34] "new york:manhattan"              "new york:main"                   "new york:staten island"         
[37] "new york:long island"            "north carolina:knotts"           "north carolina:main"            
[40] "north carolina:spit"             "north dakota"                    "ohio"                           
[43] "oklahoma"                        "oregon"                          "pennsylvania"                   
[46] "rhode island"                    "south carolina"                  "south dakota"                   
[49] "tennessee"                       "texas"                           "utah"                           
[52] "vermont"                         "virginia:chesapeake"             "virginia:chincoteague"          
[55] "virginia:main"                   "washington:san juan island"      "washington:lopez island"        
[58] "washington:orcas island"         "washington:whidbey island"       "washington:main"                
[61] "west virginia"                   "wisconsin"                       "wyoming"                        

ag$States

 [1] "#n/a"           "alabama"        "alaska"         "arizona"        "arkansas"       "california"     "colorado"      
 [8] "connecticut"    "delaware"       "florida"        "georgia"        "hawaii"         "idaho"          "illinois"      
[15] "indiana"        "iowa"           "kansas"         "kentucky"       "louisiana"      "maine"          "maryland"      
[22] "massachusetts"  "michigan"       "minnesota"      "mississippi"    "missouri"       "montana"        "nebraska"      
[29] "nevada"         "new hampshire"  "new jersey"     "new mexico"     "new york"       "north carolina" "north dakota"  
[36] "ohio"           "oklahoma"       "oregon"         "pennsylvania"   "rhode island"   "south carolina" "south dakota"  
[43] "tennessee"      "texas"          "utah"           "vermont"        "virginia"       "washington"     "west virginia" 
[50] "wisconsin"      "wyoming"       

We can see some different spelling: - e.g. “virginia:chesapeake” , “washington:main”, etc…

# split the string with : as seperator
spliteNames <- strsplit(mapStates$names, ":") 
# get first part of the origin string;
# e.g. get washington from washington:san juan island
firstPartNames <- lapply(spliteNames, function(x) x[1])  
rates <- ag$MobileHomes[match(firstPartNames, ag$States)]

Now try again:

# prepare the color mapping
cpal <- colorNumeric("Blues", rates) 
# create a blank canvas
leaflet(mapStates) %>% 
  
  # add tile
  addTiles() %>% 
  
  # draw polygons on top of the base map (tile)
  addPolygons( 
    stroke = FALSE, 
    smoothFactor = 0.2, 
    fillOpacity = 1,
    color = ~cpal(rates) # use the rate of each state to find the correct color
  )

Shapefiles

#install.packages(rdgal)
library(rgdal)

package <U+393C><U+3E31>rgdal<U+393C><U+3E32> was built under R version 3.5.3Loading required package: sp
package <U+393C><U+3E31>sp<U+393C><U+3E32> was built under R version 3.5.3rgdal: version: 1.4-3, (SVN revision 828)
 Geospatial Data Abstraction Library extensions to R successfully loaded
 Loaded GDAL runtime: GDAL 2.2.3, released 2017/11/20
 Path to GDAL shared files: C:/Users/pasulj/Documents/R/win-library/3.5/rgdal/gdal
 GDAL binary built with GEOS: TRUE 
 Loaded PROJ.4 runtime: Rel. 4.9.3, 15 August 2016, [PJ_VERSION: 493]
 Path to PROJ.4 shared files: C:/Users/pasulj/Documents/R/win-library/3.5/rgdal/proj
 Linking to sp version: 1.3-1 

#read data
world_map <- readOGR("ne_50m_admin_0_countries.shp")

OGR data source with driver: ESRI Shapefile 
Source: "C:\Users\pasulj\OneDrive - Bond University\GDDS\FIT5147\Week 3\Activities\ne_50m_admin_0_countries.shp", layer: "ne_50m_admin_0_countries"
with 241 features
It has 63 fields

head(world_map)

An object of class "SpatialPolygonsDataFrame"
Slot "data":

Slot "polygons":
[[1]]
An object of class "Polygons"
Slot "Polygons":
[[1]]
An object of class "Polygon"
Slot "labpt":
[1] -69.98268  12.52088

Slot "area":
[1] 0.01286311

Slot "hole":
[1] FALSE

Slot "ringDir":
[1] 1

Slot "coords":
           [,1]     [,2]
 [1,] -69.89912 12.45200
 [2,] -69.89570 12.42300
 [3,] -69.94219 12.43853
 [4,] -70.00415 12.50049
 [5,] -70.06611 12.54697
 [6,] -70.05088 12.59707
 [7,] -70.03511 12.61411
 [8,] -69.97314 12.56763
 [9,] -69.91182 12.48047
[10,] -69.89912 12.45200



Slot "plotOrder":
[1] 1

Slot "labpt":
[1] -69.98268  12.52088

Slot "ID":
[1] "0"

Slot "area":
[1] 0.01286311


[[2]]
An object of class "Polygons"
Slot "Polygons":
[[1]]
An object of class "Polygon"
Slot "labpt":
[1] 66.00473 33.83523

Slot "area":
[1] 62.55793

Slot "hole":
[1] FALSE

Slot "ringDir":
[1] 1

Slot "coords":
           [,1]     [,2]
  [1,] 74.89131 37.23164
  [2,] 74.84023 37.22505
  [3,] 74.76738 37.24917
  [4,] 74.73896 37.28564
  [5,] 74.72666 37.29072
  [6,] 74.66895 37.26670
  [7,] 74.55898 37.23662
  [8,] 74.37217 37.15771
  [9,] 74.37617 37.13735
 [10,] 74.49795 37.05723
 [11,] 74.52646 37.03066
 [12,] 74.54141 37.02217
 [13,] 74.43105 36.98369
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[111,] 68.21396 31.80737
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[147,] 65.96162 29.77891
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[150,] 65.18047 29.57764
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[155,] 64.52109 29.56450
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[172,] 61.78418 30.83193
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[176,] 61.66016 31.38242
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[192,] 60.71807 33.32354
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[219,] 61.08008 34.85562
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[225,] 61.10664 35.20947
[226,] 61.10000 35.27231
[227,] 61.13965 35.28887
[228,] 61.18926 35.31201
[229,] 61.19922 35.36162
[230,] 61.22568 35.42446
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[265,] 63.17891 35.85845
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[305,] 67.60742 37.22251
[306,] 67.70000 37.22725
[307,] 67.75293 37.19980
[308,] 67.75898 37.17222
[309,] 67.76602 37.14014
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[323,] 68.82373 37.27070
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[327,] 68.91182 37.33394
[328,] 68.96045 37.32505
[329,] 69.05000 37.26650
[330,] 69.18018 37.15830
[331,] 69.26484 37.10840
[332,] 69.30391 37.11694
[333,] 69.35381 37.15005
[334,] 69.41445 37.20776
[335,] 69.42969 37.29087
[336,] 69.39922 37.39932
[337,] 69.42012 37.48672
[338,] 69.49209 37.55308
[339,] 69.62578 37.59404
[340,] 69.82090 37.60957
[341,] 69.94063 37.60029
[342,] 69.98496 37.56616
[343,] 70.04473 37.54722
[344,] 70.11982 37.54351
[345,] 70.18867 37.58247
[346,] 70.25146 37.66416
[347,] 70.25498 37.76538
[348,] 70.19941 37.88604
[349,] 70.21465 37.92441
[350,] 70.23877 37.94121
[351,] 70.31328 37.98481
[352,] 70.41777 38.07544
[353,] 70.51855 38.19199
[354,] 70.61582 38.33442
[355,] 70.73594 38.42256
[356,] 70.87891 38.45640
[357,] 71.05215 38.41787
[358,] 71.25586 38.30698
[359,] 71.33271 38.17026
[360,] 71.28281 38.00791
[361,] 71.27852 37.91841
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Slot "labpt":
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Slot "ID":
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Slot "area":
[1] 3.043388


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Slot "area":
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Slot "hole":
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Slot "plotOrder":
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Slot "labpt":
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Slot "ID":
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Slot "area":
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Slot "plotOrder":
[1] 3 2 5 6 1 4

Slot "bbox":
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x -70.06611 74.89131
y -18.01973 60.40581

Slot "proj4string":
CRS arguments:
 +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0 

gdp_data <- read.csv("WorldGDP.csv")
head(gdp_data)

#match country top gdp data
rates <- gdp_data$GDP[match(world_map$admin, gdp_data$Name)]
#create the map
#set the colours
qpal <- colorQuantile("Blues",
                      rates,
                      9)
#blank canvas
leaflet(world_map) %>% #what data to use
  
  #add tile
  addTiles() %>%
  
  #draw polygons on top of base map/ tile
  addPolygons(
    stroke = FALSE,
    smoothFactor = 0.2,
    fillOpacity = 1,
    color = ~qpal(rates)
    
  )

NA

Shiny and Leaflet

Using Leaflet with Shiny

library(shiny)
ui <- fluidPage(
  
  #create map canvas on page
  leafletOutput("mymap"),
  
  #creat a button and bind it to the recalc event
  actionButton("recalc", "New points")
  
)
server <- function(input, output, session) {
  
  #event handle, thios is in case for click event
  
  points<- eventReactive(input$recalc, {
    
    #calculate normal distribution random points around melbourne
    
    cbind(rnorm(40) * 3 + 145.0431, rnorm(40) -37.8773) 
    
  }, ignoreNULL = FALSE)
  
  
  output$mymap <- renderLeaflet({ #create leaflet map
    
    #blank canvas
    leaflet() %>%
      
      #add tile
      addTiles() %>%
      
      #use radomly generated points as markers on the map
      addMarkers(data = points())
    
  })
  
}
shinyApp(ui, server)

Listening on http://127.0.0.1:5271

NA